Lung Cancer Prediction Based on Lightweight Neural Networks

As lung cancer is becoming one of the major causes of death, early detection is increasingly needed. In this study, we propose a lightweight neural network to predict lung cancer using clinical and lifestyle features, encoded from A dataset comprising 5000 samples. Our model achieves an accuracy of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{9 2 \%}$</tex>. These results illustrate the potential of deep learning methods in supporting early diagnosis of lung cancer.